This paper proposes an IoT-based fetal monitoring system using Arduino Uno, aiming to remotely monitor fetal movement, SpO2, BPM, pressure, and temperature. The system utilizes a combination of sensors including accelerometers, pulse oximeters, pressure sensors, and temperature sensors, interfaced with Arduino Uno. Data is transmitted wirelessly to a cloud server using I2C protocol for real-time monitoring and analysis.Validation tests demonstrate the system's accuracy in capturing fetal parameters and maternal vitals, enabling timely anomaly detection and intervention. The system offers a cost-effective solution for remote prenatal care, with potential applications in underserved regions. Future work involves integrating machine learning for predictive analytics and refining the user interface for improved usability.